code: def plot_resampling(X, y, sampler, ax):
      """Plot the resampled dataset using the sampler."""
      X_res, y_res = sampler.fit_resample(X, y)
      ax.scatter(
          X_res[:, 0], X_res[:, 1], c=y_res, alpha=0.8, edgecolor="k"
      )
      sns.despine(ax=ax, offset=10)
      ax.set_title(
          f"Decision function for {sampler.__class__.__name__}"
      )
      return Counter(y_res)
  
file_path: imbalanced-learn/examples/combine/plot_comparison_combine.py
imports: import matplotlib.pyplot
  import seaborn
  from sklearn.datasets import make_classification
  from collections import Counter
  import numpy
  from sklearn.linear_model import LogisticRegression
  from imblearn.combine import SMOTEENN, SMOTETomek
  from imblearn.over_sampling import SMOTE
  from imblearn.pipeline import make_pipeline
label_desc: Use image node_id 1 for calling a global function with example usage: plot_resampling(X, y, sampler, ax) and returns: Counter